A systematic review of electricity demand for large language models: evaluations, challenges, and solutions
Summary
A systematic review analyzing electricity demand, challenges, and solutions for large language models, focusing on training and inference stages.
Key quotes
"Large language models (LLMs) have revolutionized technology, but their immense electricity demand poses an urgent and critical challenge."
"The training of GPT-4 requires over 40 times more electricity than GPT-3, and inference tasks cumulatively consume substantial energy."
"Accurate evaluation of electricity demand is fraught with challenges arising from software, hardware, data centers, power grids, and external societal factors."
This report provides a detailed examination of the electricity consumption of large language models (LLMs), both in training and inference stages. It reviews current approaches to estimating energy demand, identifies key challenges in evaluation, and proposes comprehensive solutions for sustainable and efficient electricity use. The discussion includes hardware and software optimization, low-carbon energy techniques, and enhanced regulatory frameworks.